Program Evaluation and Causal Inference with R

This is the final workshop in the Georgia Policy Labs’ 2020 Summer Training series. In this workshop, you will learn about exciting new statistical methods that allow you to make causal inferences from observational data: causal diagrams (or directed acyclic graphs) and do-calculus. You will then apply this language of causal inference to program evaluation and learn how to measure the effectiveness and outcomes of social programs with several different statistical methods. This workshop was facilitated by Dr. Andrew Heiss, an assistant professor in the Department of Public Management and Policy in the Andrew Young School of Policy Studies at Georgia State University. Find more trainings on our website at https://gpl.gsu.edu/capacity-building/. Workshop materials https://talks.andrewheiss.com/2020-gpl/03_causal-inference/ Visit our website https://gpl.gsu.edu/ Follow us on Twitter https://twitter.com/GAPolicyLabs Follow us on LinkedIn https://www.linkedin.com/company/gapo... Subscribe to our newsletter http://eepurl.com/gR-gof